An experiment in causal discovery using a pneumonia database

Spirtes P, Cooper GF. An experiment in causal discovery using a pneumonia database. In: Proceedings of International Workshop in Artificial Intelligence and Statistics (1999) 162-168.

We tested a causal discovery algorithm on a database of pneumonia patients. The output of the causal discovery algorithm is a list of statements “A causes B”, where A and B are variables in the database, and a score indicating the degree of confidence in the statement. We compared the output of the algorithm with the opinions of physicians about whether A caused B or not. We found that the doctors opinions were independent of the output of the algorithm. However, an examination of the output of results suggested a simple, well motivated modification of the algorithm which would bring the output of the algorithm into high agreement with the physicians opinions.